ICCV 2017poster72 citations
Recurrent Color Constancy
Yanlin Qian, Ke Chen, Jarno Nikkanen, Joni-Kristian Kamarainen, Jiri Matas
Abstract
We introduce a novel formulation of temporal color constancy which considers multiple frames preceding the frame for which illumination is estimated. We propose an end-to-end trainable recurrent color constancy network -- the RCC-Net -- which exploits convolutional LSTMs and a simulated sequence to learn compositional representations in space and time. We use a standard single frame color constancy benchmark, the SFU Gray Ball Dataset, which can be adapted to a temporal setting. Extensive experiments show that the proposed method consistently outperforms single-frame state-of-the-art methods and their temporal variants.
BibTeX
@inproceedings{iccv2017_recurrentcolorco,
title = {Recurrent Color Constancy},
author = {Yanlin Qian and Ke Chen and Jarno Nikkanen and Joni-Kristian Kamarainen and Jiri Matas},
booktitle = {ICCV 2017},
year = {2017}
}